Specific rule setting and application method and device for medicines in intelligent medicine box, and electronic equipment

Abstract

The invention provides a specific rule setting and application method and device for intelligent medicine box medicine and electronic equipment, and belongs to the technical field of digital medicines.The method includes the steps that the medicine taking dosage and the medicine taking interval time are obtained based on medicine information data and user information data, and a basic medicine taking early warning mechanism is obtained through configuration; generating bad condition information based on the medicine specification data; generating a medicine taking specific rule according to the medicine taking dosage, the medicine taking interval time, the basic medicine taking early warning mechanism and the bad condition information; and converting the specific rule to obtain a terminal rule suitable for the intelligent medicine box equipment terminal for execution. The unified specific rule is generated based on the user information data, conversion between the specific rule and different terminal rules is achieved, on one hand, a patient can rapidly adjust the medicine taking dosage according to the state of the patient, on the other hand, medicine taking data of the unified standard can be obtained according to different intelligent medicine box data sources, and the user experience is improved. The medicine taking condition of the patient can be observed, and the illness state of the patient can be analyzed.

Description

Technical Field

[0001] The present invention relates to the field of digital medical technologies, and particularly to a method, apparatus, and electronic device for setting and applying specific rules for drugs in an intelligent medicine box. Background Art

[0002] The field of medical health has been deeply influenced by the development of social digitalization and intelligence. With the emergence of intelligent medical devices and instruments, various rich application scenarios such as sports monitoring, physical sign data monitoring, health risk assessment, and chronic disease management have been developed by driving health services with data. Among them, for chronic disease management that requires long-term medication, intelligent medicine boxes are becoming increasingly popular among patients due to functions such as timed reminder of taking medicine, management of drug dispensing, and recording of medicine-taking situations. More and more medical device manufacturers are also continuously researching and producing intelligent medicine boxes to meet the diverse needs of patients.

[0003] Currently, intelligent medicine boxes on the market mainly achieve the management and distribution of drugs through built-in sensors and intelligent control units. However, in the current intelligent medicine box specifications, there is no unified rule for the management of specific drug dosages and times, resulting in some special medicine-taking patients being unable to accurately, quickly, and effectively adjust their medicine-taking dosages. Moreover, due to differences in the formats of drug-taking dosages and times defined by devices produced by different manufacturers, data conversion from different intelligent medicine box data sources may result in data distortion or even conversion errors, thus affecting the analysis of patients' conditions and being unfavorable for doctors to observe patients' conditions and give accurate treatment suggestions. Summary of the Invention

[0004] To solve the above problems, in order to enable patients to conveniently and quickly adjust their medicine-taking dosages according to their own conditions, and to accurately convert data from different data sources into available standardized data, the present invention provides a method, apparatus, and electronic device for setting and applying specific rules for drugs in an intelligent medicine box, sets medicine-taking conversion rules for different intelligent medicine box device terminals, and converts drug-taking dosages and times with different rules into standard specific rules, so as to obtain unified standard data for different rules of data from multiple intelligent medicine box device terminals.

[0005] In the first aspect, the present invention provides a method for setting and applying specific rules for drugs in an intelligent medicine box, adopting the following technical solution.

[0006] A method for setting and applying specific rules for drugs in an intelligent medicine box includes:

[0007] Obtaining the medicine-taking dosage and medicine-taking interval time based on medicine information data and user information data, and configuring a basic medicine-taking warning mechanism;

[0008] Generate adverse condition information indicating the risk of taking medicine for the user based on the medicine instruction data;

[0009] Generate specific medicine-taking rules according to the medicine-taking dose, medicine-taking interval, basic medicine-taking warning mechanism and adverse condition information;

[0010] Convert the specific rules to obtain terminal rules applicable to the intelligent medicine box device terminal for execution.

[0011] Furthermore, the obtaining of the medicine-taking dose and medicine-taking interval based on the medicine information data and user information data includes:

[0012] Pre-configure a medicine information database and a user information database;

[0013] Call the data in the medicine information database and obtain the medicine-taking dose data through calculation based on the pharmacology model;

[0014] Call the data in the user information database and obtain the medicine-taking interval data through calculation based on the physiological parameters.

[0015] Furthermore, the obtaining of the medicine-taking dose and medicine-taking interval based on the medicine information data and user information data, and configuring the basic medicine-taking warning mechanism includes:

[0016] Call the data in the user information database and configure the basic medicine-taking warning mechanism through calculation based on the physiological parameters and setting of parameter thresholds to remind the user to take medicine on time

[0017] Furthermore, the generating of the adverse condition information indicating the risk of taking medicine for the user based on the medicine instruction data includes:

[0018] Pre-configure a medicine instruction database;

[0019] Call the data in the medicine instruction database and generate adverse condition information through natural language processing and knowledge extraction.

[0020] Furthermore, before generating the specific medicine-taking rules according to the medicine-taking dose, medicine-taking interval, basic medicine-taking warning mechanism and adverse condition information, obtain the processing rules for special situations of medicine-taking dose changes, including:

[0021] Call the data in the medicine information database and obtain the processing rules for special situations through calculation based on the pharmacology model.

[0022] Furthermore, before obtaining the medicine-taking dose and medicine-taking interval based on the medicine information data and user information data, preprocess the original medicine information, including:

[0023] Extract and analyze the original medicine information to obtain structured medicine information;

[0024] Standardize and verify the parsed drug information, including filling in missing values, converting units, and validating the legality of drug numbers.

[0025] Further, generating specific medication rules based on the medication dosage, medication interval, basic medication warning mechanism, and adverse condition information includes:

[0026] Obtain the information reported by the intelligent medicine box device terminal, and generate specific rules based on the information reported by the intelligent medicine box device terminal.

[0027] In a second aspect, the present invention provides a device for setting and applying specific rules for drugs in an intelligent medicine box, adopting the following technical solution.

[0028] A device for setting and applying specific rules for drugs in an intelligent medicine box includes a medication basic data acquisition module, an adverse condition information generation module, a specific rule generation module, and a rule conversion module, wherein:

[0029] The medication basic data acquisition module is used to obtain the medication dosage, medication interval, and basic medication warning mechanism of a specific drug.

[0030] The adverse condition information generation module is used to generate adverse condition information indicating the medication risk of the user.

[0031] The specific rule generation module is used to generate specific medication rules based on the obtained medication dosage, medication interval, basic medication warning mechanism, and generated adverse condition information.

[0032] The rule conversion module is used to implement the conversion between specific rule data and terminal rule data of the intelligent medicine box device terminal through conversion rules.

[0033] Further, a special situation handling rule acquisition module is used to obtain special situation handling rules for the medication of special populations with changes in medication dosage / or medication interval.

[0034] The specific rule generation module is used to generate specific medication rules based on the obtained medication dosage, medication interval, basic medication warning mechanism, generated adverse condition information, and obtained special situation rule handling module.

[0035] In a third aspect, the present invention provides an electronic device, a processor, and a memory. The memory stores a computer-executable program, and the processor executes the computer-executable program to implement:

[0036] Obtain the medication dosage and medication interval based on drug information data and user information data, and configure a basic medication warning mechanism.

[0037] Generate adverse condition information indicating the risk of taking medicine for the user based on the medicine instruction data;

[0038] Generate specific medicine-taking rules according to the medicine-taking dose, medicine-taking interval, basic medicine-taking warning mechanism, and adverse condition information;

[0039] Convert the specific rules to obtain terminal rules applicable to the intelligent medicine box device terminal for execution.

[0040] By providing a method, device, and electronic device for setting and applying specific rules for intelligent medicine box drugs, the present invention generates unified specific rules based on medicine information data and user information data. On the one hand, since the setting of the specific rules refers to the information of the user himself, patients can quickly adjust the medicine-taking dose according to their own status. On the other hand, on the premise of setting unified data standards, the data collected by the intelligent medicine box is standardized. The medicine-taking data information of unified standards is obtained after the data from different intelligent medicine box data sources are converted according to the conversion rules, meeting the quality requirements of specific rule data, which is conducive to observing the patient's medicine-taking situation and analyzing the patient's condition; in addition, the specific rules can be updated according to the information reported by the intelligent medicine box, so that patients can update their medicine-taking plans according to their own conditions, which helps to continuously improve patient compliance. Description of the Drawings

[0041] Figure 1 It is a schematic diagram of the cloud platform and the intelligent medicine box device terminal of the method for setting and applying specific rules for intelligent medicine box drugs in Embodiment 1 of the present invention.

[0042] Figure 2 It is a schematic diagram of the intelligent medicine box device terminal of the method for setting and applying specific rules for intelligent medicine box drugs in Embodiment 1 of the invention.

[0043] Figure 3 It is a code schematic of the specific rules of the method for setting and applying specific rules for intelligent medicine box drugs in Embodiment 1 of the invention.

[0044] Figure 4 It is a code schematic of the terminal rules of the method for setting and applying specific rules for intelligent medicine box drugs in Embodiment 1 of the invention.

[0045] Figure 5 It is a structural schematic diagram of the device for setting and applying specific rules for intelligent medicine box drugs in Embodiment 3 of the invention.

[0046] Description of the reference numerals: 10. Medicine-taking basic data acquisition module; 20. Adverse condition information generation module; 30. Special situation processing rule acquisition module; 40. Specific rule generation module; 50. Rule conversion module. Detailed Description of the Invention

[0047] The following will describe the invention in detail in conjunction with specific embodiments and the attached Figures 1-5 drawings, so that those skilled in the art can more fully understand the purpose, features and effects of the present invention.

[0048] Unless otherwise defined, all technical and scientific terms used in the present invention have the same meaning as commonly understood by those skilled in the art to which the present invention belongs. When the definitions of terms in this specification conflict with the commonly understood meanings of those skilled in the art to which the present invention belongs, the definitions in this specification shall prevail.

[0049] By providing a method, device, and electronic device for setting and applying specific rules for drugs in an intelligent medicine box, the present invention standardizes, unifies, and standardizes data from different intelligent medicine box device terminals, enabling the rapid formation of decision-making data useful for patient treatment, thereby achieving the purpose of rapidly and continuously optimizing the diagnosis and treatment means.

[0050] Embodiment 1

[0051] As a specific embodiment of the present invention, this embodiment provides a method for setting and applying specific rules for drugs in an intelligent medicine box. The method is completed between the cloud platform and the intelligent medicine box device terminal. Referring to Figure 1 、 Figure 2 , the specific steps are as follows:

[0052] S1. Obtain the dosage and dosing interval, and configure the basic medication warning mechanism

[0053] On the cloud platform, the dosage and dosing interval are set for different drugs. There are a drug information database and a user information database configured on the cloud platform. The specific drug dosage and dosing interval are obtained by calling the drug information data in the drug information database and the user information data in the user information database. The acquisition methods of the data in the user information database include, but are not limited to, collection from the intelligent medicine box device terminal, active provision by the user through the application information collection program, and integration of medical institution medical record data. The user information obtained through the above methods is configured in the user information database, and other medical institution medical records are legally obtained data.

[0054] Among them, the drug information database stores detailed information about drugs, including:

[0055] Drug name: The generic name and possible brand names of the drug;

[0056] Pharmacological parameters: The pharmacological properties of the drug, such as half-life, metabolic pathway, and bioavailability;

[0057] Dosage information: Recommended dosage, maximum dosage, minimum dosage;

[0058] Drug interactions: Information on the interactions of drugs with other drugs, foods, or chemicals;

[0059] Adverse reactions: Adverse reactions and side effects that a drug may cause;

[0060] Drug label: Detailed description of a drug, including uses, indications, contraindications, and precautions;

[0061] Special medication rules: Medication rules for specific situations, such as medication regimens for special populations.

[0062] The user information database stores information related to users, including:

[0063] Basic user information: Including the user's name, age, and gender;

[0064] Physiological parameters: The user's physiological indicators, such as blood pressure, heart rate, and blood sugar;

[0065] Health history: Including the user's disease history and allergy information;

[0066] Medication history: The user's past medication records, including the name of the drug, dosage, and medication time;

[0067] Special needs: Requirements for special medication rules, such as the need for timed reminders and special medication regimens;

[0068] Medical records: Relevant archival information of the user in a medical institution.

[0069] Specifically, the cloud platform of this embodiment can be an AIoT Internet of Things platform. On the cloud platform, the data of the drug information database is called, and calculations are performed based on a pharmacology model to obtain medication dose data, and the medication dose is stored in numerical form on the cloud platform; the data of the user information database is called, and calculations are performed based on physiological parameters to obtain medication interval time data, and the medication interval time is stored in time form on the cloud platform.

[0070] Among them, the pharmacology model includes but is not limited to bioavailability, drug metabolism, and drug distribution models. The pharmacology model in this embodiment uses the existing models in the prior art.

[0071] Similarly, the medication interval time calculated based on physiological parameters depends on the physiological parameters adopted and the purpose of taking the medication. The physiological parameters can be heart rate, blood pressure, and blood sugar, and the purpose of taking the medication can be to keep the heart rate within a certain range and lower the blood pressure to a certain value. The physiological parameter calculation method in this embodiment can adopt the existing solutions in the prior art, and no new physiological parameter calculation method will be provided separately.

[0072] In practical applications, the pharmacological models and physiological parameter calculation methods adopted in this embodiment can be adjusted as needed.

[0073] The dosage and dosing interval are the basic data for taking medicine executed by the intelligent medicine box, indicating how much medicine to take at what interval.

[0074] The basic medicine-taking warning mechanism is used to remind users to take medicine on time. By determining the user's physiological parameter indicators and the indicator thresholds, the user's physiological parameters are from the user information database. When the actual value of the user's physiological parameter indicator reaches the threshold condition, the reminder function of the basic medicine-taking warning mechanism will be activated, and a medicine-taking reminder will be sent to the user terminal. Specifically, the cloud platform calls the data of the user information database, and based on the calculation of physiological parameters and the determination of reminder conditions, the configuration of the basic medicine-taking warning mechanism is completed, and the basic medicine-taking warning mechanism is stored in the cloud platform in the form of reminder rules.

[0075] Specifically, the basic medicine-taking warning mechanism includes:

[0076] Medicine-taking time setting: For each medicine, set the user's medicine-taking time, which can be a specific time point or a specific time period;

[0077] Physiological parameter setting: Determine the parameters used to monitor the user's physiological condition, such as blood pressure, heart rate, and blood sugar;

[0078] Threshold condition setting: For specific physiological parameters, set the threshold conditions for triggering a reminder. When the user's physiological parameters reach or exceed the set threshold, a reminder is triggered;

[0079] Reminder rule configuration: According to the setting of physiological parameters and threshold conditions, determine the reminder rules, that is, when to trigger a reminder, in what way to remind, and the content of the reminder;

[0080] Reminder method setting: Set the specific reminder method, such as mobile application notifications, text messages, and emails, to ensure that users receive reminders in a timely manner.

[0081] According to the basic medicine-taking warning mechanism, when the user's physiological parameter indicator reaches the threshold condition, remind the user to take medicine, and then conduct medicine-taking reminders according to the obtained dosing interval; when the user's physiological parameter indicator does not reach the threshold condition, do not remind the user to take medicine.

[0082] The basic medicine-taking warning mechanism can remind users to take medicine according to the set time. Especially for the elderly, long-term patients, or users who need complex medication regimens, it can avoid the situation of forgetting to take medicine or missing the medicine-taking time.

[0083] To ensure the reliability of obtaining the medication dose and interval, as well as setting up the basic medication warning mechanism, and to avoid data errors, data verification and exception handling are carried out on the cloud platform. Also, to ensure the stability and security of operation, backup, disaster recovery, and access permission settings are carried out in parallel on the cloud.

[0084] S2. Generate adverse condition information for different drugs

[0085] Adverse condition information refers to the harmful reactions that may occur to the human body after taking drugs, including drug allergy and side effect reaction information, which is used to indicate the risks existing in the process of drug use. The purpose of generating adverse condition information is to warn users when taking drugs.

[0086] Specifically, a drug instruction manual database is pre-configured on the cloud platform. When generating adverse condition information, the data in the drug instruction manual database is called, and natural language processing is performed on the drug instruction manual information. Then, knowledge extraction is performed on the result of the natural language processed drug instruction manual information, and knowledge information including the drug name, corresponding adverse condition information, applicable population, and emergency symptoms is extracted. After knowledge extraction processing, adverse condition information for different drugs is generated. In this embodiment, the adverse condition information of different drugs is stored in the form of a hash table, where key-value pairs are used to store the drug name and the adverse condition information of the drug, realizing the correspondence between the drug name and the adverse condition information.

[0087] In other embodiments, the adverse condition information of different drugs can also be collected from web content through web crawlers, and the collected information is processed through natural language processing to convert unstructured data into structured data.

[0088] In this embodiment, the generated adverse condition information is saved in the adverse condition information library.

[0089] S3. Obtain special case handling rules

[0090] In this embodiment, the special case handling rule refers to the medication plan used to treat specific populations, so as to meet the medication needs of different populations. For example, for a drug, its dosage changes during the medication period and is not fixed. In one example, for the drug ensartinib hydrochloride, the starting dosage for users is 225 mg once a day; the first reduction is to 200 mg once a day; the second reduction is to 150 mg once a day, rather than maintaining the dosage of 225 mg once a day all the time. Therefore, in this embodiment, for the situation where the medication dosage and / or the medication interval changes during the medication period, special case handling rules are obtained.

[0091] In S1, the dosage and dosing interval obtained through pharmacology models and physiological parameters are fixed values, belonging to the conventional dosing rules, and such conventional dosing rules cannot meet the dosing requirements of specific populations for variable dosages and dosing intervals. In S3, in order to meet the dosing requirements of specific populations, considering the improvement of the physical condition and the changes in the condition during the medication period, a dosing rule with dynamically changing dosage and / or dosing interval is formulated.

[0092] The special case handling rules not only involve changes in the dosage, but may also involve changes in the dosing interval. In one possible case, both the dosage and the dosing interval change simultaneously. The special case handling rules are set to adapt to individual differences, physiological changes or certain special circumstances that may occur during the medication period of users.

[0093] Specifically, on the cloud platform, data in the drug information database is called, calculations are performed based on pharmacology models, configuration data of the special case handling rules is obtained, and a medication plan is formed to guide the medication of special populations. The special case handling rules are stored in the form of medication rules on the cloud platform. Based on the existing pharmacology models, the drug concentrations of patients at different dosages and different time intervals are predicted, so as to guide the medication rules in special circumstances.

[0094] In another embodiment, the acquisition of the special case handling rules further includes calling clinical trial data and expert experience data. By observing the reactions of patients in clinical trials or actual medication, data on individual differences and changes of patients and expert experience data are collected, and the collected data on individual differences and changes and expert experience data are called to form the special case handling rules.

[0095] In one embodiment, the acquisition of the special case handling rules further includes calling personalized medical data based on the patient himself, such as genetic information, physiological parameters, and changes in the condition, and obtaining the special case handling rules through data analysis and machine learning.

[0096] In one embodiment, the acquisition of the special case handling rules further includes calling existing case data, and obtaining special medication rules applicable to different situations based on the data analysis of existing cases in special circumstances.

[0097] In other embodiments, the special case handling rules are stored in the form of a database form, and fields and data are used to store the parameters and content of the special case handling rules respectively, so as to better reflect the corresponding relationship between the special case handling rules and the specific medication plan of users. Since the special case handling rules can be applied to the dosing requirements of specific populations, the medication effect of users is ensured.

[0098] Similar to the processing of obtaining the medication dosage, medication interval, and the basic medication warning mechanism in S1, to ensure the correct execution of the special situation handling rules and avoid data errors, data verification and exception handling are performed when running the special situation handling rules on the cloud platform; and to ensure the stability and security of the operation, backup, disaster recovery, and permission settings are carried out on the cloud platform.

[0099] S4. Generate specific rules for different intelligent medicine box device terminals and send the terminal medication plan to the intelligent medicine box device terminals

[0100] In this embodiment, based on the medication dosage, medication interval obtained in S1, the configured basic medication warning mechanism, the adverse condition information generated for different drugs in S2, and the special situation handling rules obtained in S3, a unified medication specific rule located on the cloud platform is generated. The specific rule refers to the medication rules used to guide users to take medicine, which are all standardized. The specific rule standardizes the data in the same data format, and a medication plan is formed based on the specific rule.

[0101] Based on the medication specific rule on the cloud platform, it is sent to the corresponding intelligent medicine box device terminal. Different intelligent medicine box device terminals obtain the terminal medication plan sent by the cloud platform and matching the terminal rules of the corresponding intelligent medicine box device terminal, which is used to guide and remind users to take medicine.

[0102] The terminal medication plan is obtained through the conversion of the specific rule. Specifically, conversion rules are configured for different intelligent medicine box device terminals on the cloud platform. The conversion rules are used to convert the specific rule based on the cloud platform into a terminal rule that meets the requirements of the intelligent medicine box device terminal, and then the terminal medication plan is obtained, meeting the medication specifications of the intelligent medicine box device terminal. And the conversion rules can convert the terminal medication information collected by the intelligent medicine box device terminal into data in a standardized format that meets the specific rule. The cloud platform configures corresponding conversion rules for different types of intelligent medicine box device terminals to achieve data transmission between the intelligent medicine box device terminal and the cloud platform.

[0103] Use the conversion rules to convert the specific rule set on the cloud platform to obtain a terminal medication plan that can be executed by the intelligent medicine box device terminal. When the cloud platform obtains the information of the intelligent medicine box device terminal, the data information of different intelligent medicine box device terminals is converted into standardized data that meets the requirements of the specific rule of the cloud platform through the conversion rules.

[0104] This embodiment further illustrates the conversion rules using the specific drug ensartinib hydrochloride capsules as an example. Ensartinib hydrochloride capsules are an anti-tumor drug that inhibits the growth and proliferation of cancer cells by blocking the activation of the cell signaling pathway, thereby achieving the purpose of anti-cancer treatment.

[0105] The conversion rules in this embodiment involve the content as shown in Table 1-5.

[0106] Table 1 Examples of biochemical indicators involved in the conversion rules

[0107]

[0108]

[0109] Table 2 Examples of medication content in the conversion rules

[0110]

[0111]

[0112] Among them, the examples given in Table 1 are the conversion rules for biochemical indicators, which are used to convert the biochemical indicator data such as ALT and SAT collected from the intelligent medicine box device terminal into the format specified in the specific rules of the cloud platform. The condition name, condition identifier, and condition items are used to represent specific biochemical indicators and corresponding conditions.

[0113] In Table 1, the condition name represents the conceptual category of the condition; the condition identifier is used to uniquely identify the condition; the condition item represents the specific entries that make up a condition. A condition contains one or more entries and is used to represent the structured data in the condition; the condition item name is used to distinguish condition items; the condition item value description represents the specific description of the content and is used to elaborate on the specified content of the condition entry. It is possible to determine whether the biochemical indicator is within the normal range or exceeds the threshold based on the condition item value, so as to carry out subsequent warnings or reminders.

[0114] Table 2 specifically shows examples of the dosage and administration time of medications.

[0115] In the specific rules, some data codes are as follows:

[0116] drugsn represents the drug serial number and is the unique identifier of the drug;

[0117] drugname represents the generic name or trade name of the drug;

[0118] drugtype represents the drug classification, such as Western medicine, traditional Chinese medicine, etc.;

[0119] drugcureid represents the drug treatment disease number and indicates the disease that the drug is mainly used to treat;

[0120] drugpoorcondition represents adverse condition information;

[0121] poorid represents the adverse condition information number and indicates a specific drug adverse reaction;

[0122] The poortype indicates the type of adverse condition information, such as diarrhea, dizziness, etc.;

[0123] The poornote indicates the matters needing attention for adverse condition information and the written description of adverse reactions;

[0124] The poorresult indicates the processing result of adverse condition information, such as seeking medical treatment, stopping taking medicine, etc.;

[0125] The drugspecialrule indicates the processing rules for special situations of drugs and the matters needing attention for specific drugs;

[0126] The specialruleid indicates the number of the processing rule for special situations and the unique identifier of the special rule;

[0127] The specialruletype indicates the type of the processing rule for special situations, such as taking on an empty stomach, contraindications, etc.;

[0128] The specialrulenote indicates the description of the matters needing attention for the processing rule of special situations;

[0129] The specialrule indicates the content of the processing rule for special situations and the specific description of the rule;

[0130] The specialruleresult indicates the processing result of the processing rule for special situations, such as executed, not executed, etc.

[0131] In this embodiment, the specific rule data adopts the JSON format. After the data from different intelligent medicine box device terminals is preprocessed by the corresponding conversion rules, it all becomes JSON structured data, thus facilitating the analysis and processing of the data obtained from different intelligent medicine box device terminals. The cloud platform adopts the JSON format data, which also facilitates the configuration of specific rules. In other embodiments, the specific rule data can also adopt the XML format.

[0132] Add drug information to the drug information database of the cloud platform, as shown in Table 3.

[0133] Table 3 Drug Information of Ensartinib Hydrochloride Capsules

[0134]

[0135] The added drug information includes drug name, treatment category, specialized type, special type, drug SN, so that the cloud platform can correctly understand and process.

[0136] The format of the converted drug adverse condition information is shown in Table 4.

[0137] Table 4 Adverse Condition Information of Ensartinib Hydrochloride Capsules

[0138]

[0139] Table 4 gives an example of the conversion rules for adverse condition information. The adverse information conversion rules are used to convert the adverse condition information data uploaded from the intelligent medicine box device terminal into the standard format specified in the specific rules of the cloud platform. The converted adverse condition information includes drug SN, adverse type, location, description, and dose adjustment. The conversion rules ensure that the content related to the adverse condition information of the drug is correctly mapped to the corresponding fields defined in the special rules of the cloud platform, enabling the cloud platform to understand and process it.

[0140] As shown in Table 4, for the adverse condition information of ensartinib hydrochloride capsules, the location "lungs" is mapped to the "poortype" field in the special rules, and "ALT or AST increased to >3×ULN, accompanied by an increase in total bilirubin >2×ULN" is mapped to the "poornote" field.

[0141] The conversion rules for special cases are shown in Table 5.

[0142] Table 5 Special case handling rules for ensartinib hydrochloride capsules

[0143]

[0144] The conversion of special case handling rules is used to convert the special case handling rules uploaded from the intelligent medicine box device terminal into the standard format specified in the specific rules of the cloud platform. The converted special case handling rule information includes drug SN, case type, description, trigger condition, and dose adjustment. The conversion rules ensure that the content related to the special case handling rules of the drug is correctly mapped to the corresponding fields defined in the special rules of the cloud platform, enabling the cloud platform to understand and process it.

[0145] As shown in Table 5 for the special case handling rules of ensartinib hydrochloride capsules, "forgetting to take medicine at the specified time" is mapped to the "specialrulenote" field in the specific rules, and "if one dose of this product is missed and the time interval from the missed dose to the next dose is more than 12 hours" is mapped to the "specialrule" field.

[0146] The above conversion principle ensures that the data uploaded from different intelligent medicine box device terminals can be uniformly understood and processed on the cloud platform, and at the same time, it is also convenient for the configuration and management of specific rules.

[0147] The data format of the special rules generated on the cloud platform for the above example is as Figure 3 shown. The data format after conversion and sent to the intelligent medicine box device terminal is as Figure 4As shown in the figure. During the conversion, type conversion and business encapsulation are performed on the bad condition information and special case handling rules. In the converted format, the bad condition information (drugpoorcondition) and special case handling rules (drugspecialrule) are presented in the format of an object.

[0148] Embodiment 2

[0149] As a specific embodiment of the present invention, this embodiment provides a method for setting and applying specific rules for drugs in an intelligent medicine box. The method is completed between a cloud platform and an intelligent medicine box device terminal. On the basis of Embodiment 1, it further includes:

[0150] S0. Preprocess the original drug information to obtain standardized drug information data

[0151] Extract and analyze the original information fields including the drug manufacturer and number uploaded by the intelligent medicine box device terminal to obtain key information including the drug name and drug specification in a structured form;

[0152] Standardize and verify the parsed drug key information, including filling in missing values, converting units, and verifying the legality of the drug number, to obtain drug information data in a unified JSON or XML message format.

[0153] Through the above preprocessing of the original drug information, the standardization of heterogeneous original drug data is achieved, meeting the requirements of specific rule setting for drug information data, and facilitating the invocation of drug information data in the drug information database.

[0154] Through the above processing, the drug information stored in the drug information database can be standardized, facilitating invocation and avoiding errors or failures during invocation.

[0155] Furthermore, referring to Figure 2 , it further includes S5 to obtain the information reported by the intelligent medicine box device terminal, and obtain specific rules based on the information reported by the intelligent medicine box device terminal.

[0156] The information reported by the intelligent medicine box device terminal includes various data generated during the operation of the intelligent medicine box device terminal, such as the number of times the medicine box is opened, the medication object, and the medication time, collectively referred to as user behavior information. Preferably, the information reported by the intelligent medicine box device terminal to the cloud platform is first preprocessed and converted into structured data that meets the requirements of the cloud platform through conversion rules, such as converted into JSON format data, to facilitate the cloud platform to identify and analyze the reported information.

[0157] Specifically, S5 includes at least S51 for obtaining the initialization information of the intelligent medicine box device terminal, S52 for obtaining the medication-taking plan sent by the cloud platform, and S53 for obtaining the user behavior information of the intelligent medicine box device terminal.

[0158] S51. Obtain the initialization of the intelligent medicine box device terminal

[0159] In this embodiment, when the intelligent medicine box device terminal is in use, it is necessary to synchronize the medication-taking plan obtained from the cloud platform. Therefore, when using the intelligent medicine box device terminal, the device information is initialized first, including the basic usage dosage and timing reminder of the medicine, the interpretation of adverse condition information, the processing flow of special situation handling rules, and the initialization of warning information. The above information is associated with the identification of different drugs. When the user uses the medicine, the intelligent medicine box device terminal can judge the medicine attributes according to the above information.

[0160] S52. Obtain the medication-taking rules sent by the cloud platform

[0161] Send a data synchronization request to the cloud platform through the intelligent medicine box device terminal;

[0162] When the cloud platform receives the synchronization request sent by the intelligent medicine box device terminal, it calls the latest specific rule data for specific drugs on the cloud platform, including the medication dosage, medication interval, timing reminder, adverse condition information, and special situation handling rules, and structurally processes the latest specific rule data;

[0163] The cloud platform updates the medication-taking plan according to the latest specific rule data and sends it to the intelligent medicine box device terminal through a secure transmission protocol. The intelligent medicine box device terminal uses the latest medication-taking plan sent by the cloud platform as the terminal medication-taking plan to guide the user to take medicine.

[0164] The user can regularly obtain the latest medication-taking plan from the cloud platform through the intelligent medicine box device terminal to automatically update the terminal medication-taking plan, obtain the updated medication dosage, medication interval, adverse condition information, and special situation handling rules, and use the updated terminal medication-taking plan to guide taking medicine to meet the latest medication requirements and improve the effectiveness of taking medicine.

[0165] S53. Obtain the user behavior information of the intelligent medicine box device terminal and issue a medication-taking plan based on the user behavior information

[0166] The intelligent medicine box device terminal records the user behavior information through sensors. When the user performs precise operations on the intelligent medicine box device terminal, the user's behavior information is recorded by the intelligent medicine box device terminal and reported to the cloud platform, enabling the cloud platform to understand the user's behavior. The reporting frequency can be achieved by setting a timing rule or reported in real time when the user operates the intelligent medicine box device terminal, enabling the cloud platform to understand the user's behavior in real time.

[0167] When there is enough behavioral information of different users for a certain drug collected, it can provide a reference for formulating a more reasonable medication-taking plan for the general public. Since the cloud platform can collect a large amount of users' behavioral information regarding a specific drug through the intelligent medicine box device terminal, the cloud platform can analyze the large amount of users' behavioral information data collected. The users' behavioral information can reflect the medication-taking characteristics of users with different diseases. By using machine learning algorithms to analyze the large amount of users' behavioral information data, based on the characteristics of different diseases, a standard disease model is established. The disease model can reflect the medication-taking behavior of users suffering from a specific disease. Since the cloud platform continuously collects and obtains users' behavioral information, it can continuously iterate the disease model, generate a disease model library, and obtain a more personalized medication guidance plan that matches the users with specific diseases according to the disease model library, which helps to continuously improve patients' compliance.

[0168] Specifically, when the cloud receives the users' behavioral information and the initialization information on the intelligent medicine box terminal device, based on the users' behavioral information and the initialization information, the drug ID is obtained. Then, according to the matching situation of the drug ID, the users' behavioral information, and the initialization information of the intelligent medicine box terminal device, a personalized medication plan including new dose / interval setting, adverse condition information, and special situation handling rules is generated, and the personalized medication plan is stored in the disease model library and sent to the intelligent medicine box device terminal.

[0169] Furthermore, after obtaining the drug ID, the drug information database is called, and the basic information, properties, and taboos of the drug are queried according to the drug ID. Combining with the users' previous medical records in the user information database, the disease development stage and individual reactions of the users are judged. Integrating the drug information, the users' physical signs information and the condition information in the user information database, a personalized medication plan for the users is generated. Then, the personalized medication plan is converted into executable rule parameters, and formatted data operations are performed to form a personalized medication plan that meets the specific rule requirements of the cloud platform; the formatted personalized medication plan is stored in the disease model library, and then the formatted personalized medication plan is sent to the users' intelligent medicine box device terminal to update the terminal medication plan and guide the users to take medicine.

[0170] In this embodiment, after the cloud platform receives the users' behavioral information sent by the intelligent medicine box device terminal, it can generate new specific rules that are more in line with the users' conditions by combining the drug dose, medication interval, adverse condition information, and special situation handling rules. The users can choose to obtain new medication rules according to their own medication-taking situation and physical state, which facilitates the users to adjust the medication dose and medication interval, improves the medication effect, and avoids the situation of overmedication or undermedication.

[0171] Embodiment 3

[0172] As a specific embodiment of the present invention, this embodiment provides a device for setting and applying specific rules for drugs in an intelligent medicine box. The device is used to implement the method in Embodiment 1 and includes: a medication basic data acquisition module 10, an adverse condition information generation module 20, a special situation processing rule acquisition module 30, a specific rule generation module 40, and a rule conversion module 50.

[0173] The medication basic data acquisition module 10 acquires the medication dose, medication interval time, and basic medication warning mechanism for specific drugs by the user. Among them, the medication dose is obtained by calling the drug information database, and the medication time interval is obtained by calling the user information database.

[0174] The adverse condition information generation module 20 is used to generate adverse reaction information for specific drugs. By calling the data in the drug instruction manual database, natural language processing is performed on the drug instruction manual information, and then knowledge extraction is performed on the result of the natural language processed drug instruction manual information to generate adverse condition information for different drugs after the knowledge extraction process.

[0175] The special situation processing rule acquisition module 30 is used to obtain special situation processing rules for the medication of special populations with changes in the medication dose / or medication interval time.

[0176] The specific rule generation module 40 is used to generate unified specific rules based on the obtained medication dose, medication interval time, basic medication warning mechanism, generated adverse condition information, and obtained special situation processing rules.

[0177] The rule conversion module 50 is used to implement the conversion of specific rule data and terminal rule data of the intelligent medicine box device terminal through conversion rules.

[0178] Before the medication plan that conforms to the generated specific rules is sent to the intelligent medicine box device terminal, the medication plan is converted into a terminal medication plan that conforms to the terminal rules through conversion rules, and the intelligent medicine box device terminal executes the terminal medication plan to guide the user to take medicine.

[0179] When the cloud platform acquires the information of the intelligent medicine box device terminal, the data information of different intelligent medicine box device terminals is converted into standardized data that meets the specific rule requirements of the cloud platform through conversion rules.

[0180] This embodiment also includes a drug information preprocessing module, which is used to extract, analyze, and standardize the original information fields including the drug manufacturer and number uploaded by the intelligent medicine box device terminal.

[0181] The reported information acquisition and processing module acquires the reported information of the intelligent medicine box device terminal and obtains specific rules according to the information reported by the intelligent medicine box device terminal.

[0182] Through the device in this embodiment, the setting of specific rules for specific drugs in the intelligent medicine box can be realized, and the medication plan formed according to the specific rules can be quickly sent to different intelligent medicine box device terminals to guide users to take medicine. It can also convert the data collected by different intelligent medicine box device terminals into standardized data in a specific rule format for convenient analysis and use.

[0183] Embodiment 4

[0184] As a specific embodiment of the present invention, this embodiment provides an electronic device, including:

[0185] One or more processors for processing computer programs, including computer programs stored in the memory or stored on the memory to display graphical information of the GUI on an external input / output device;

[0186] One or more memories for storing computer programs executed by the processor, so that the processor executes the methods for setting and applying specific rules for drugs in the intelligent medicine box in Embodiments 1 and 2;

[0187] Component connection interfaces;

[0188] And a bus connecting each component.

[0189] The electronic device in this embodiment solves the problem of the lack of unified rules for specific drug doses and times in the existing intelligent medicine box by executing the methods for setting and applying specific rules for drugs in the intelligent medicine box, realizes the medication management of different intelligent medicine boxes by setting specific rules, and can obtain standardized record data of users' medication.

[0190] The above is only a preferred embodiment of the present invention, and it is not any other form of limitation to the present invention. Any modification or equivalent change made according to the technical essence of the present invention still belongs to the scope protected by the present invention.

Claims

1. A method for setting and applying specific rules for drugs in an intelligent medicine box, characterized in that, The method includes: Obtaining the dosage and dosing interval based on drug information data and user information data, and configuring a basic medication warning mechanism; Generating adverse condition information indicating the user's medication risk based on drug instruction data; Generating specific medication rules according to the dosage, dosing interval, basic medication warning mechanism, and adverse condition information; Converting the specific rules to obtain terminal rules applicable to the intelligent medicine box device terminal for execution.

2. The method for setting and applying specific rules for drugs in the intelligent medicine box according to claim 1, characterized in that The obtaining of the dosage and dosing interval based on drug information data and user information data includes: Pre-configuring a drug information database and a user information database; Invoking the data in the drug information database and obtaining dosage data through calculation based on a pharmacology model; Invoking the data in the user information database and obtaining dosing interval data through calculation based on physiological parameters.

3. The method for setting and applying specific rules for drugs in the intelligent medicine box according to claim 2, characterized in that, The obtaining of the dosage and dosing interval based on drug information data and user information data, and configuring a basic medication warning mechanism, includes: Invoking the data in the user information database, configuring a basic medication warning mechanism based on the calculation of physiological parameters and the setting of parameter thresholds to remind the user to take medicine on time.

4. The method for setting and applying specific rules for drugs in the intelligent medicine box according to claim 1, characterized in that The generating of adverse condition information indicating the user's medication risk based on drug instruction data includes: Pre-configuring a drug instruction database; Invoking the data in the drug instruction database and generating adverse condition information based on natural language processing and knowledge extraction.

5. The method for setting and applying specific rules for drugs in the intelligent medicine box according to claim 2, characterized in that, Before generating specific medication rules according to the dosage, dosing interval, basic medication warning mechanism, and adverse condition information, obtaining special case handling rules for dosage changes, including: Invoking the data in the drug information database and obtaining special case handling rules through calculation based on a pharmacology model.

6. The method for setting and applying specific rules for drugs in the intelligent medicine box according to claim 1, characterized in that, Before obtaining the dosage and dosing interval based on drug information data and user information data, preprocessing the original drug information, including: Extracting and parsing the original drug information to obtain structured drug information; Performing standardization and verification on the parsed drug information, including filling in missing values, converting units, and verifying the legality of drug numbers.

7. The method for setting and applying specific rules for drugs in the intelligent medicine box according to claim 1, characterized in that, The generating of specific medication rules according to the dosage, dosing interval, basic medication warning mechanism, and adverse condition information includes: Obtaining the reported information of the intelligent medicine box device terminal and generating specific rules according to the reported information of the intelligent medicine box device terminal.

8. A device for setting and applying specific rules for drugs in an intelligent medicine box, characterized in that, It includes a medication basic data acquisition module (10), an adverse condition information generation module (20), a specific rule generation module (40), and a rule conversion module (50), where: The medication basic data acquisition module (10) is used to obtain the dosage and dosing interval of a specific drug and the basic medication warning mechanism; The adverse condition information generation module (20) is used to generate adverse condition information indicating the user's medication risk; The specific rule generation module (40) is used to generate specific medication rules according to the obtained dosage, dosing interval, basic medication warning mechanism, and generated adverse condition information; The rule conversion module (50) is used to convert specific rule data into terminal rule data of the intelligent medicine box device terminal through conversion rules.

9. The setting and application device for specific rules of drugs for the intelligent medicine box according to claim 8, characterized in that, It also includes: A special situation handling rule acquisition module (30) for obtaining special situation handling rules for the medication of special populations with changes in medication dosage and / or medication interval time; The specific rule generation module (40) is used to generate medication specific rules according to the obtained medication dosage, medication interval time, basic medication warning mechanism, generated adverse condition information, and the obtained special situation rule processing module.

10. An electronic device, characterized in that, It includes a processor and a memory, and a computer executable program is stored on the memory. The processor executes the computer executable program to implement the method for setting and applying the specific rules for the intelligent medicine box drugs according to any one of claims 1-7.

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